Background: This research, part of a doctoral study, aims to examine the impact of managerial factors on the implementation of Infection Prevention and Control (IPC) measures in Israeli hospitals. The study focuses on identifying key facilitators and barriers from the perspectives of physician and nurse managers, with an emphasis on understanding the integration of managerial strategies and theoretical frameworks in IPC implementation. Objective: The objective is to explore specific managerial factors, both facilitators and barriers, influencing the effective implementation of IPC measures. The research investigates these influences through the lens of physicians and nurses managing IPC units in public hospital settings. Methodology: A mixed-method approach was adopted, involving in-depth interviews with ten IPC-Unit managers (five physicians and five nurses) and a comprehensive questionnaire distributed among IPC-Unit heads. The study’s demographic and professional profiles of participants are detailed in Table 1. The data collection process encompassed an Activity Assessment Questionnaire (2-AAQ) and an Organizational Change Implementation Questionnaire (3-OrgChangeImplQ), with the distribution of responses categorized by implementation stages and sociological theories (Tables 2-4). Result: Managerial autonomy emerged as a significant catalyst for IPC implementation, with supportive leadership and resource allocation being critical. Differences in approaches between physician and nurse managers were observed, reflecting diverse strategies in planning, execution, monitoring, and maintenance of IPC measures. The findings also revealed a natural alignment with sociological theories, particularly Normalization Process Theory (NPT) and Diffusion of Innovations (DOI), despite a lack of formal training in these areas. Conclusions: The study underscores the multifaceted nature of IPC implementation, highlighting the importance of managerial autonomy, supportive leadership, and a deep understanding of organizational culture. The inherent alignment of IPC strategies with NPT and DOI theories suggests the potential of these frameworks in guiding IPC implementation. The research advocates for the integration of these theoretical perspectives into formal training programs to enhance the effectiveness of IPC measures in healthcare settings.

Shark vertebrae and their centra (vertebral bodies) are high-performance structures able to survive millions of cycles of high amplitude strain despite lacking a repair mechanism for accumulating damage. Shark centra consist of mineralized cartilage, a biocomposite of bioapatite (bAp), and collagen, and the nanocrystalline bAp's contribution to functionality remains largely uninvestigated. Using the multiple detector energy-dispersive diffraction (EDD) system at 6-BM-B, the Advanced Photon Source, and 3D tomographic sampling, the 3D functionality of entire centra were probed. Immersion in ethanol vs phosphate-buffered saline produces only small changes in bAp d-spacing within a great hammerhead centrum. EDD mapping under in situ loading was performed an entire blue shark centrum, and 3D maps of bAp strain showed the two structural zones of the centrum, the corpus calcareum and intermedialia, contained opposite-signed strains approaching 0.5%, and application of ~8% nominal strain did not alter these strain magnitudes and their spatial distribution.

In order to improve the positioning accuracy of industrial robots, this paper proposes a global calibration method for planar parallel robot considering joint errors, which solves the problem that the existing calibration methods only consider part of the error sources and the calibration accuracy is poor, and improves the calibration efficiency and robot positioning accuracy. Consequently, it improves calibration efficiency and the overall precision of robot positioning. Firstly, the error model of overdetermined equations combined with structural parameters is established, and the global sensitivity of each error source is analyzed. Based on the measurement data of laser tracker, the local error source is identified by the least square method, which improves the local error accuracy by 88.6%. Then, a global error spatial interpolation method based on inverse distance weighting method is proposed, and the global accuracy is improved by 59.16%. Finally, the radial basis function neural network error prediction model with strong nonlinear approximation function is designed for global calibration, and the accuracy is improved by 63.05%. Experimental results verify the effectiveness of the proposed method. This study not only provides technical support for the engineering application of this experimental platform but also provides theoretical guidance for the improvement of the accuracy of related robot platforms.

Unmanned aerial vehicles (UAVs) have recently been widely applied in a comprehensive realm. By enhancing computer photography and artificial intelligence, UAVs can automatically discriminate against environmental objectives and detect events that occur in the real scene. The application of collaborative UAVs will offer diverse interpretations which support a multiperspective view of the scene. Due to the diverse interpretations of UAVs usually deviating, UAVs require a consensus interpretation for the scenario. This study presents an original consensus-based method to pilot multi-UAV systems for achieving consensus on their observation as well as constructing a group situation-based depiction of the scenario. Taylor series are used to describe the fuzzy nonlinear plant and derive the stability analysis using polynomial functions, which have the representations $V(x )={m_{\textrm{1} \le l \le N}}({{V_\textrm{l}}(x )} )$ and ${V_l}(x )={x^T}{P_l}(x )x$. Due to the fact that the ${\dot{P}_l}(x )$ in ${\dot{V}_l}(x )={\dot{x}^T}{P_l}(x )x + {x^T}{\dot{P}_l}(x )x + {x^T}{P_l}(x )\dot{x}$ will yield intricate terms to ensure a stability criterion, we aim to avoid these kinds of issues by proposing a polynomial homogeneous framework and using Euler's functions for homogeneous systems. First, this method permits each UAV to establish high-level conditions from the probed events via a fuzzy-based aggregation event. The evaluated consensus indicates how suitable is the scenario collective interpretation for every UAV perspective.

Accidents are a prevalent feature of working in the maritime industry. While studies have shown to what extent accidents and fatalities have occurred, the current research has generally been limited to commercial shipping. There is nearly no academic research focusing on the safety issues in the superyacht industry. This paper analyses the importance of promoting safety culture in the superyacht industry, the role of maritime legislation in maintaining safety and the role of Port State Control in ensuring all legislation is implemented. It aims to provide a critical examination of safety culture in the superyacht industry and evaluate the appropriateness for further measures to ensure safe working practices. It found out that while some superyachts do maintain an effective safety system, there remains almost 50% of the investigated fleet that do not promote the desired safety culture. It becomes evident that complacency and poor education contribute to the reduced and limited safety culture. The lack of education and awareness is demonstrated when the study shows individuals believing they maintain good safety practices but still admitting to taking various life-threatening risks.

This study conducts particle-resolved direct numerical simulations to analyse how finite-size spherical particles affect the decay rate of turbulent kinetic energy in non-sustained homogeneous isotropic turbulence. The decaying particle-laden homogeneous isotropic turbulence is generated with two set-ups, i.e. (1) releasing particles into a single-phase decaying homogeneous isotropic turbulence and (2) switching off the driving force of a sustained particle-laden homogeneous isotropic turbulence. With both set-ups, the decay of turbulent kinetic energy follows a power-law when the flow is fully relaxed, similar to their single-phase counterparts. The dependence of the power-law decay exponent $n$ on the particle-to-fluid density ratio, particle size and volume fraction is also investigated, and a predictive model is developed. We find that the presence of heavier particles slows down the long-time power-law decay exponent.

We present evidence revealing that an object with specific properties can exhibit multiple stable falling postures at low Reynolds numbers. By scrutinizing the force equilibrium relationship of a fixed object at various attack angles and Reynolds numbers, we introduce a methodology that can obtain the stable falling postures of the object. This method saves computational resources and more intuitively presents the results in the full parameter domain. Our findings are substantiated by free-fall tests conducted through both physical experiments and numerical simulations, which validate the existence of multiple stable solutions in accordance with the interpolation results obtained with fixed objects. Additionally, we quantify the abundance and distribution patterns of stable falling postures for a diverse range of representative shapes. This discovery highlights the existence of multiple stable solutions that are universally present across objects of different shapes. The implications of this research extend to the design, stability control and trajectory prediction of all free and controlled flights in both air and water.

We establish some inequalities that arise from truncating Lerch sums and derive uniform asymptotic formulae for the spt-crank of ordinary partitions. The uniform asymptotic formulae improve upon a result of Mao [‘Asymptotic formulas for spt-crank of partitions’, J. Math. Anal. Appl. 460(1) (2018), 121–139].

The mean flow in a turbulent boundary layer (TBL) deviates from the canonical law of the wall (LoW) when influenced by a pressure gradient. Consequently, LoW-based near-wall treatments are inadequate for such flows. Chen et al. (J. Fluid Mech., vol. 970, 2023, A3) derived a Navier–Stokes-based velocity transformation that accurately describes the mean flow in TBLs with arbitrary pressure gradients. However, this transformation requires information on total shear stress, which is not always readily available, limiting its predictive power. In this work, we invert the transformation and develop a predictive near-wall model. Our model includes an additional transport equation that tracks the Lagrangian integration of the total shear stress. Particularly noteworthy is that the model introduces no new parameters and requires no calibration. We validate the developed model against experimental and computational data in the literature, and the results are favourable. Furthermore, we compare our model with equilibrium models. These equilibrium models inevitably fail when there are strong pressure gradients, but they prove to be sufficient for boundary layers subjected to weak, moderate and even moderately high pressure gradients. These results compel us to conclude that history effects in mean flow, which negatively impact the validity of equilibrium models, can largely be accounted for by the material time derivative term and the pressure gradient term, both of which require no additional modelling.

As the need for collaboration across multiple organizations to deal with complex social issues such as poverty, crime, and public health grows, Public–Private Partnership (PPP) is of increasing importance. However, little is known about when and why private firms engage in such partnerships. Drawing on upper-echelon theory and the information-processing perspective, we highlight the importance of institutional knowledge and information embedded in CEO cross-sector work experience. We argue that such tacit knowledge and information enables CEOs to better identify the potential risks associated with PPPs. Consequently, CEOs with cross-sector work experience tend to be more cautious in participating in such partnerships, especially in developing economies like China, where private actors face greater information incompleteness concerning post-collaboration hazards due to the government's selective disclosure. Moreover, we develop a multi-moderator framework in which regional marketization and political connection alter the main effect by serving as supplementary information channels for private actors. A panel dataset of Chinese private listed firms from 2013 to 2021 provides strong support for our hypotheses. This study contributes to our understanding of the micro-foundation of PPP formation and draws attention to CEOs’ prior career experiences in different organizational forms.

A cycle C of a graph G is dominating if $V(C)$ is a dominating set and $V(G)\backslash V(C)$ is an independent set. Wu et al. [‘Degree sums and dominating cycles’, Discrete Mathematics 344 (2021), Article no. 112224] proved that every longest cycle of a k-connected graph G on $n\geq 3$ vertices with $k\geq 2$ is dominating if the degree sum is more than $(k+1)(n+1)/3$ for any $k+1$ pairwise nonadjacent vertices. They also showed that this bound is sharp. In this paper, we show that the extremal graphs G for this condition satisfy $(n-2)/3K_1\vee (n+1)/3K_2 \subseteq G \subseteq K_{(n-2)/3}\vee (n+1)/3K_2$ or $2K_1\vee 3K_{(n-2)/3}\subseteq G \subseteq K_2\vee 3K_{(n-2)/3}.$

Accurate online estimation of the payload parameters benefits robot control. In the existing approaches, however, on the one hand, only the linear friction model was used for online payload identification, which reduced the online estimation accuracy. On the other hand, the estimation models contain much noise because of using actual joint trajectory signals. In this article, a new estimation algorithm based on parameter difference for the payload dynamics is proposed. This method uses a nonlinear friction model for the online payload estimation instead of the traditionally linear one. In addition, it considers the commanded joint trajectory signals as the computation input to reduce the model noise. The main contribution of this article is to derive a symbolic relationship between the parameter difference and the payload parameters and then apply it to the online payload estimation. The robot base parameters without payload were identified offline and regarded as the prior information. The one with payload can be solved online by the recursive least squares method. The dynamics of the payload can be then solved online based on the numerical difference of the two parameter sets. Finally, experimental comparisons and a manual guidance application experiment are shown. The results confirm that our algorithm can improve the online payload estimation accuracy (especially the payload mass) and the manual guidance comfort.

In an isolate-free graph G, a subset S of vertices is a semitotal dominating set of G if it is a dominating set of G and every vertex in S is within distance 2 of another vertex of S. The semitotal domination number of G, denoted by $\gamma _{t2}(G)$, is the minimum cardinality of a semitotal dominating set in G. Goddard, Henning and McPillan [‘Semitotal domination in graphs’, Utilitas Math. 94 (2014), 67–81] characterised the trees and graphs of minimum degree 2 with semitotal domination number half their order. In this paper, we characterise all graphs whose semitotal domination number is half their order.

In this paper, an unmanned bicycle (UB) with a reaction wheel is designed, and a second-order mathematical model with uncertainty is established. In order to achieve excellent balancing performance of the UB system, an adaptive controller is designed, which is composed of nominal feedback control, compensating control using extreme learning machine observer and reaching control via integral terminal sliding mode (ITSM) and barrier function (BF)-based adaptive law. Owing to the features of BF-based ITSM (BFITSM), not only any uncertainty or disturbance upper bound is not needed any longer but also the finite-time convergence of the closed-loop system can be ensured with a predefined error bound. Moreover, the BF-based control gain can be adaptively adjusted according to the update of the lumped uncertainty such that the overestimation is removed. The stability analysis of the closed-loop system is given according to Lyapunov theory. Comparable experimental results on an actual UB are carried out to validate the superior balancing performance of the proposed controller.

Understanding the yield attributes of rice crops grown at super high-yielding sites is useful for identifying how to achieve super high yield in rice. In this study, field experiments were conducted in 2021 and 2022 to compare grain yield and yield attributes of ten high-yielding hybrid rice varieties between Xingyi (a super high-yielding site) and Hengyang (a site with typical yields). Results showed that Xingyi produced an average grain yield of 13.4 t ha−1 in 2021 and 14.0 t ha−1 in 2022, which were, respectively, 20% and 44% higher than those at Hengyang. Higher panicles per m2 and higher grain weight were responsible for the higher grain yield at Xingyi compared to Hengyang. The higher values of panicles per m2 and grain weight at Xingyi compared to Hengyang were due to greater source capacity resulting from improved pre-heading biomass production. This study suggests that simultaneously increasing panicle number and grain weight through improving pre-heading biomass production is a potential way to achieve super high yield in rice.